OverviewWe are designing the grid of the future!
Responsibilities
Join us in leading thechange!
We are seeking aPower Systems Optimization Engineer to join the EPE software team. This role pairs transmission planning expertise with mathematical optimization to solve some of the hardest problems in grid planning: selecting least-cost, technically sufficient mitigation portfolios and quantifying their economic value.
You will design, prototype, and productionize optimization methods for problems that are large, non-linear, and mixed-integer by nature, such as choosing which network upgrades, storage, or operational measures resolve violations across many scenarios and contingencies. You'll work closely with planners, software developers, and product owners to turn these methods into reliable tools inside our planning platform.
Howyou can make an impact:
- Mitigation portfolio optimization: Formulate and solve problems that select least-cost combinations of transmission upgrades, storage, reconfiguration, and other mitigations to resolve thermal, voltage, and stability violations across multiple cases, seasons, and contingencies.
- Economic analysis: Build methods for cost allocation, benefit-cost and production-cost-informed evaluation, and comparison of alternative portfolios to support planning and interconnection decisions.
- Non-linear & mixed-integer modeling: Develop MILP/MINLP formulations, AC/DC power flow relaxations and linearizations (e.g., DC/PTDF, LODF, SOCP), decomposition approaches (e.g., Benders), and heuristics that scale to large real-world systems.
- Algorithm development to production: Prototype in Python, validate against full AC power flow results from industry tools, and work with developers to deploy methods as robust, scalable services.
- Validation & benchmarking: Verify that optimized portfolios solve the violations when re-simulated; quantify optimality gaps, runtime, and sensitivity to assumptions.
- Collaboration: Partner with transmission planners to capture real-world constraints (lead times, outage feasibility, cost estimates, planning criteria) and translate them into model constraints and objectives.
- Client support & communication: Explain optimization results, trade-offs, and assumptions to engineers, clients, and stakeholders; support onboarding and tailored deployments.
- Documentation: Write methodology papers, model formulations, and validation reports that help engineers and clients trust the results.
Qualifications
Bring your passion, here's whats needed:
- Master's degree or PhD in Electrical Engineering, Operations Research, Applied Mathematics, or a related field, with a focus on power systems and/or optimization. A Bachelor's with equivalent experience will be considered.
- 3+ years of experience applying optimization to power systems problems (e.g., transmission expansion planning, optimal power flow, unit commitment, resource or portfolio planning), in industry or research.
- Strong foundation in mathematical optimization: linear, mixed-integer, and non-linear programming, convex relaxations, and decomposition methods.
- Proficiency in Python and at least one optimization modeling framework (e.g.,Pyomo, JuMP, CVXPY, PuLP, gurobipy) and commercial or open-source solvers (e.g., Gurobi, CPLEX, Xpress, HiGHS, Ipopt).
- Solid understanding of power flow, contingency analysis, and transmission planning concepts, including the US transmission system and ISO/RTO structures.
- Strong communication skills: able to explain complex models, assumptions, and results to engineers and non-technical audiences.
- Excellent problem-solving skills, especially in diagnosing infeasibility, numerical issues, and scaling challenges in large models.
Preferred Qualifications:
- Hands-on transmission planning or interconnection study experience (steady-state, short circuit, dynamic stability) using tools such as PSS/E, PSLF,PowerWorld, TSAT, or TARA.
- Experience with transmission expansion planning, network upgrade cost allocation, or interconnection cluster studies (e.g., SPP DISIS, MISO DPP, PJM cycle studies).
- Experience with production cost or capacity expansion models (e.g., PLEXOS, PROMOD,GridView, Aurora, PowerSIMM) and economic planning metrics (APC, adjusted production cost, benefit-cost ratios).
- Experience with stochastic or robust optimization and scenario-based planning under uncertainty.
- Familiarity with power systems optimization packages (e.g.,PowerModels.jl, pandapower, PyPSA, MATPOWER).
- Software engineering practices: Git, testing (pytest), code review, and deploying models in cloud or distributed environments.
- Knowledge of machine learning methods used to accelerate optimization (e.g., surrogate models, warm-starting, constraint screening).
- Publications or open-source contributions in power systems optimization.
How we support you:
- Comprehensive health and wellness benefits including medical, dental, and vision with 100% premium coverage foryou
- Generous PTO and paid holidays
- MyShare Employee Ownership Program
- Work with industry leaders
- 401K, up to a 4% match (100% vested from day 1)
Location: This position will be Remote.
Travel: Occasional travel may be needed (10% or less)
